[Tutor] Adding a new row to the dataframe with datetime as index

[Peter Otten]

Asif Iqbal wrote:

> Hi,
> 
> I am trying to add a new row to a new date in the dataframe like below
> 
>    df.loc['2018-01-24'] = [0,1,2,3,4,5]
> 
> And I am getting the following error
> 
>   ValueError: cannot set using a list-like indexer with a different length
> than the value
> 
> I do have the right number of columns and I can lookup a row by the date
> 
>   df.loc['2018-01-23']
> 
>   df.shape
>   (8034, 6)
> 
>   df.index
>   DatetimeIndex(['2018-01-23', '2018-01-22', '2018-01-19', '2018-01-18',
>                '2018-01-17', '2018-01-16', '2018-01-12', '2018-01-11',
>                '2018-01-10', '2018-01-09',
>                ...
>                '1986-03-25', '1986-03-24', '1986-03-21', '1986-03-20',
>                '1986-03-19', '1986-03-18', '1986-03-17', '1986-03-14',
>                '1986-03-13', '2018-01-24'],
>               dtype='datetime64[ns]', name='date', length=8034, freq=None)
> 
> Any idea how to add a new row to a new date?

My experiments indicate that there may be multiple values with the same key:

> >>> import pandas as pd
>>> df = pd.DataFrame([[1,2], [3,4], [5,6], [7,8]], index=["a", "b", "a", 
"a"])    
>>> df.loc["a"]
   0  1
a  1  2
a  5  6
a  7  8

[3 rows x 2 columns]
>>> df.loc["a"] = [10, 20]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib/python3/dist-packages/pandas/core/indexing.py", line 98, in 
__setitem__
    self._setitem_with_indexer(indexer, value)
  File "/usr/lib/python3/dist-packages/pandas/core/indexing.py", line 422, 
in _setitem_with_indexer
    self.obj._data = self.obj._data.setitem(indexer, value)
  File "/usr/lib/python3/dist-packages/pandas/core/internals.py", line 2396, 
in setitem
    return self.apply('setitem', *args, **kwargs)
  File "/usr/lib/python3/dist-packages/pandas/core/internals.py", line 2376, 
in apply
    applied = getattr(blk, f)(*args, **kwargs)
  File "/usr/lib/python3/dist-packages/pandas/core/internals.py", line 615, 
in setitem
    raise ValueError("cannot set using a list-like indexer "
ValueError: cannot set using a list-like indexer with a different length 
than the value

If found two ways to resolve this, 

(1) the obvious, ensure that the lengths are the same:

>>> df.loc["a"] = [[10, 20], [30, 40], [50, 60]]
>>> df
    0   1
a  10  20
b   3   4
a  30  40
a  50  60

(2) pass the key as a tuple:

>>> df.loc["a",] = [1000, 2000]
>>> df
      0     1
a  1000  2000
b     3     4
a  1000  2000
a  1000  2000

[4 rows x 2 columns]

I suspect that you want neither, and instead avoid duplicate keys.